New dataset

To create a new dataset:

1. At the top left of the Drive, click New and select New dataset.
2. The New dataset wizard opens.

The following steps compose the New dataset creation workflow:

• 1. Dataset creation
• 2. Image selection
• 3. Processing template
• 4. GCPs automation

1. Dataset creation

In the Dataset creation section,

1. (For Pix4Dcloud users) Enter the dataset's name.
   (For Pix4Dcloud Advanced users) Assign the dataset to an existing site or create a new one.
2. Choose one of the following options:
   a) Upload images for processing
   b) Upload processed results

Upload images for processing

The images that will be uploaded as a new dataset will be processed to generate the photogrammetric outputs defined in step 3. Processing template and that will be displayed on the web platform.

1. Click Next to continue.
2. Follow the instruction for step 2. Image selection.

Upload processed results

1. Once selected Upload processed results, select Create to create the dataset.
2. Upload the single outputs. More information in: How to upload results and outputs to Pix4Dcloud.

The following steps are not available for uploaded outputs.

2. Image selection

1. Drag and drop the images or search for the folder where they are stored. More information about input requirements in: Inputs.
2. (Optional) To add more images drag and drop additional images or click Select images and browse to the folder where the additional images are stored.
3. (Optional) Delete some images if necessary.
4. Select Next and follow the instructions for step 3. Processing template.

3. Processing template

This step allows the user to select a processing template for the project. Different processing templates are available:

• 3D maps: Generates the Point Cloud, 3D Textured Mesh, Orthomosaic, and DSM. Ideal for aerial images acquired using a grid flight plan with high overlap, mostly oriented towards the ground. Typical applications are quarries, cadasters, etc.
  The quality needed for the outputs can be specified between:
• Quality: Good output quality with high accuracy. Processing times longer than the Rapid option are expected.
• Rapid: Lower output quality. Faster for assessing the quality of the acquired dataset.

• 2D orthomosaic: Generates the Orthomosaic. Ideal for aerial images acquired using a grid flight plan with high overlap on flat terrain, for example, agricultural fields.
  The quality needed for the outputs can be specified between:
• Quality: Good output quality with high accuracy. Processing times longer than the Rapid option are expected.
• Rapid: Lower output quality. Faster for assessing the quality of the acquired dataset.

• 3D models: Generates 3D Textured Mesh, and Point Cloud. Ideal for any images with a high amount of overlap such as images taken from the ground or oblique aerial images (free flight). Application examples are 3D models of buildings, objects, ground imagery, indoor imagery, inspection, etc.
  The quality needed for the outputs can be specified between:
• Quality: Good output quality with high accuracy. Processing times longer than the Rapid option are expected.
• Rapid: Lower output quality. Faster for assessing the quality of the acquired dataset.

• AG multispectral: Generates the NDVI map for precision agriculture. Ideal for aerial images from multispectral cameras with band-dedicated sensors, acquired at high overlap using a grid flight plan.

Once the processing template has been selected:

1. (For Pix4Dcloud users) Select Create to finalize the dataset creation. The upload of the inputs starts.
   (For Pix4Dcloud Advanced users) Select Next and follow the instructions for step 4. GCPs automation.

4. GCPs automation

If the user intends to use the GCP autodetection functionality

The CSV file containing the GCP data has to be uploaded. Follow the instructions in AutoGCPs detection functionality.

If the GCPs automation step is not needed

1. Click Skip and process.

The project starts processing to finalize the dataset creation. The upload of the inputs to the server is started.